The new mandate for CIOs in the age of AI

Enterprise AI has decisively moved from experimentation to expectation. What was once a series of pilots and proofs of concept (POC) is now considered a core driver of enterprise value.

Boards are no longer asking if the organization has an AI strategy, they are asking when it will translate into measurable results. CEOs expect AI to create durable differentiation and business leaders expect to see AI everywhere: powering personalization, enabling data-driven products, improving operational efficiency, and unlocking new revenue streams.

And increasingly, they expect CIOs to make it all work.

This is the new mandate for CIOs in the age of AI: deliver tangible business impact by scaling AI across the enterprise. This stands in addition to other key responsibilities like strengthening data integrity, modernizing fragmented technology stacks, and eliminating the operational friction that slows execution.

It is a mandate defined by tension. CIOs are being asked to move faster, even as risk, regulatory scrutiny, and organizational complexity continue to rise. AI capabilities have advanced at extraordinary speed, but the enterprise foundations required to support them i.e. governed data, consistent user permissions, reliable data pipelines, and cross-functional alignment have not kept pace.

The result is a widening gap between what AI promises and what enterprises can actually deploy. For today’s CIO, closing that gap has become a critical responsibility going into 2026.

AI changed the CIO remit—quietly, then all at once

For years, CIO success was measured by stability and efficiency: keeping systems running, managing costs, and modernizing infrastructure on predictable timelines. AI has fundamentally changed that calculus.

Today, CIOs are accountable for outcomes that sit at the intersection of technology, data, governance, and growth. They are expected to:

• Scale AI and personalization consistently across brands, regions, and channels
• Enable data-driven products and entirely new revenue lines
• Increase speed to market without increasing risk or regulatory exposure
• Ensure enterprise-wide data integrity, access, and trust
• Modernize legacy stacks that were never designed for real-time, AI-driven decision-making

These expectations go well beyond traditional IT stewardship. They place CIOs at the center of the company’s ability to compete, making them responsible for turning data into an asset and AI into a repeatable, enterprise capability—one that can be deployed safely, governed consistently, and scaled without friction.

That shift in responsibility is where many organizations are struggling. The ambition is clear and the demand is real. But the foundations required to deliver on it—governed data, consistent permissions, and architectures built for scale—are often missing.

Why AI momentum stalls inside the enterprise

AI pilots are easy to launch. Fully scaled enterprise AI is not.

Across large, multi-brand organizations, CIOs see the same pattern play out again and again. Teams build models quickly, POCs work in controlled environments, and early demos generate enthusiasm and executive buy-in. Then comes the hard part: scaling.

When AI needs to operate across regions, brands, channels, and systems—using real consumer data under real regulatory constraints—progress slows. Timelines stretch, confidence erodes, and initiatives that looked promising in isolation struggle to as they're pushed out to the full enterprise.

The issue is not a lack of ambition, investment, or technical talent. Rather, it’s the reality of the enterprise environment:

• Fragmented data ecosystems spread across legacy and modern systems
• Inconsistent user permissions and consent signals that can’t be trusted at scale
• Manual data plumbing and brittle integrations that don’t hold up in production
• Slow, reactive privacy and compliance reviews driven by uncertainty
• Limited data lineage and auditability across brands, regions, and vendors

AI doesn’t fail at the model layer. It fails at the systems and governance layer through which data flows, permissions are enforced, and risk is managed.

This reality is what makes AI the new CIO mandate. The success or failure of enterprise AI increasingly depends on whether these leaders can modernize their organization's data foundations—removing the friction that prevents AI from scaling safely and predictably.

The real work of leading in the AI era

To lead in the AI era, CIOs must focus on a different set of priorities and go beyond infrastructure upgrades or isolated tools.

1. Treat user data permissions as core infrastructure

AI can only scale on data that is fully-permissioned for use. That means that user preferences and consent choices can’t live in silos, spreadsheets, or point solutions. They must be normalized, enforced, and updated in real-time across every system, from CDPs and data warehouses to AI pipelines and personalization platforms.

2. Eliminate manual data plumbing

Custom scripts and one-off integrations don’t scale in an AI-first enterprise—every manual workflow becomes a bottleneck, while every brittle integration becomes a risk. CIOs leading in the AI era focus on automation at the systems layer, reducing engineering overhead and making governance repeatable.

3. Build trust into the data foundation

AI success depends on building data trust across legal, privacy, security, engineering, and the business.

That trust comes from visibility, including clear lineage, real-time enforcement, and seamless auditability. When stakeholders can see how data moves, where it’s used, and whether it’s permissioned, compliance reviews move faster and teams like privacy and legal are able to act as business enablers.

4. Design for scale across brands and regions

Multi-brand, global enterprises can’t afford bespoke governance for every system or market. CIOs must establish a “deploy once, scale everywhere” model where new AI tools, regions, or brands inherit the same enterprise-wide data controls automatically. This is how AI stops being a series of localized wins and becomes an full enterprise capability.

The CIO opportunity: Turning governance into growth

The most effective CIOs don’t treat governance, privacy, and compliance as blockers to innovation. Rather, they recognize these motions as valuable prerequisite steps.

When user data is fragmented and permissions are unclear, teams move slowly because there's no other option. Reviews drag on, risk increases, and innovation slows. But when the user-data foundation is unified, automated, and enforced at the systems layer, an entirely new dynamic emerges.

With a modern, AI-ready data foundation in place:

• AI initiatives move from pilot to production with far less friction
• Personalization improves because teams have access to trusted, fully permissioned data
• New revenue programs, such as Retail Media Networks (RMN) and AI-powered experiences, scale consistently across brands and regions
• Engineering teams spend their time building products, not maintaining brittle data plumbing
• Risk decreases as compliance becomes proactive and systemic, rather than reactive and manual

In this environment, AI stops being experimental. It becomes an operationalized, repeatable capability the business can rely on.

That is the real mandate for CIOs in the age of AI: not just to enable innovation, but to build the governed data foundation that allows innovation to scale with confidence.

Leading the next phase of enterprise AI

As AI becomes embedded in every part of the enterprise, the margin for error narrows. Scale demands more than powerful models, it demands trust in the data that feeds them. CIOs who lead in this moment will be the ones to modernize how their organizations manage user data: from permissions and access to enforcement and governance.

This shift turns fragmented stacks into cohesive platforms. It replaces manual reviews and one-off fixes with automated, system-level controls. And it transforms friction across privacy, security, engineering, and product teams into sustained momentum.

The models are ready. The opportunity is clear. Now the foundation has to catch up—and CIOs are the leaders positioned to make that happen.